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首页> 外文期刊>IEEE transactions on dependable and secure computing >SADI: A Novel Model to Study the Propagation of Social Worms in Hierarchical Networks
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SADI: A Novel Model to Study the Propagation of Social Worms in Hierarchical Networks

机译:SADI:研究分层网络中社会蠕虫传播的新型模型

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As more and more people rely on social networks for business and life, social worms constitute one of the major security threats to our society. Modern social worms exhibit two new features, message notification and the temporal characteristic of human mobility. Message notification indicates a user will get a reminder once a new message comes to a social account. The temporal characteristic of human mobility indicates a user can operate corresponding computer in different locations with different resting time. Previous scholars have proposed some analytical models for the propagation dynamics of social worms. However, they did not consider the above two features and there is one critical problem unrealized, which is structural imperfection of network topology. Previous models have not taken into account the hierarchical topology structure, which results from a many-to-many relationship between users and hosts. To address these problems, we model propagation dynamics of social worms oriented hierarchical networks in this paper, and the proposed model accurately describes the propagation behavior of social worms. We conduct both a theoretical analyses and extensive simulations to show our model can overcome inaccuracy in the number of infected nodes and provide a stronger approximation for the worm propagation. The results show that our model presented in this paper achieves a greater accuracy in characterizing the propagation of modern social worms.
机译:随着越来越多的人依靠社交网络开展业务和生活,社交蠕虫构成了对我们社会的主要安全威胁之一。现代社交蠕虫具有两个新功能,即消息通知和人类活动的时间特征。消息通知表明,一旦有新消息发送到社交帐户,用户将收到提醒。人流动的时间特性表明用户可以在具有不同休息时间的不同位置操作相应的计算机。先前的学者为社交蠕虫的传播动力学提出了一些分析模型。但是,他们没有考虑上述两个功能,并且存在一个尚未实现的关键问题,这是网络拓扑的结构缺陷。先前的模型没有考虑分层拓扑结构,该分层拓扑结构是由用户和主机之间的多对多关系导致的。为了解决这些问题,我们在面向社交蠕虫的分层网络中对传播动力学进行建模,并且该模型准确地描述了社交蠕虫的传播行为。我们进行了理论分析和广泛的模拟,以表明我们的模型可以克服受感染节点数量的不准确性,并为蠕虫的传播提供了更强的近似性。结果表明,本文提出的模型在表征现代社会蠕虫的传播方面具有更高的准确性。

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